sharing myself...

I was searching information about particular products in
various E-Commerce websites and after a couple of searches, I could notice a
side bar recommending some products based on the search I made. The product
list was comprising similar products so that of I searched. Looking at how these kind of recommendations are done, got to know that it is an another
world full of algorithms.

The recommendation is done based on some set of machine
learning algorithms to make the life simple. The machine learning algorithms
makes use of information such as products searched, country where the customer
lives in etc., In sophisticated E-Commerce systems having option of user
registration will consider the facts such as user age group, gender of user. In simple, a set of algorithms will gather information based on the search
history of user, analyze the gathered information and then recommend products
to the user, such type of recommending mechanism is called as Recommender Systems.

Recommender systems is an emerging field even though
conventional method of suggesting a product either positively or negatively do
exists from quite a long time. (Best example is recommending friends for a
movie!)

Pros:

1) Easy recommendations make less searchs and some times end up
un good deals

2) User eviews will give accurate information, this is also an
advantae if you purchase online as you can see other reviews too, most of the
times honest

3) Speed up the process of decision and purchase based on the
previous statistics

Cons:

1) If the system recomends products with bias, then customer
wil be landing into wrong deals

2) Chances are that some websites may suggest products wrongly
based on analysis of little information gathered